The goal of biomedical cancer research is to uncover perturbations in important pathways that lead to tumor disease states so that therapeutic treatments may be designed. It is clear that most cancers are caused by alterations at one or more levels of the genetic program. Only through simultaneous monitoring of DNA, RNA, and protein can the comprehensive understanding of underlying processes occurring in these multifactorial diseases be made. While there is a great need to integrate data derived from functional genemic experiments with that ascertained from patient-derived clinical data, it is usually beyond the scope of most clinicians and researchers to effectively perform this task alone. Thus, the aims of this core are to establish a novel relational database to simultaneously store and interlink functional genomic datasets with clinicopathological patient data and gene annotation, to develop innovative analytical and visualization tools for integrated analysis of these data, and to provide these applications to investigators who are involved in clinical and/or molecular cancer research. Such combinatorial, visual and statistical analyses will result in the better understanding of the complex pathophysiology of tumorigenesis and will facilitate the identification of potential diagnostic markers and therapeutic targets for these diseases.